Computational Materials Science: Modeling Materials

Predict and understand material properties through atomistic simulations with the powerful computational chemistry package Amsterdam Modeling Suite (AMS). Speed up research and development of new catalysts, polymers, batteries, and organic electronics through materials modeling. AMS is easy to install, offers molecular (ADF) and periodic density functional theory (BAND, interface to Quantum ESPRESSO and VASP), fast tight-binding (DFTB) and semi-empirical (MOPAC) modules, reactive force fields (ReaxFF), and machine learning potentials.

The integrated graphical user interface as well as through flexible scripting for high-throughput and advanced workflows help you set up and analyze your calculations. The central AMS Driver takes care of advanced potential energy surface exploration tasks (optimizations, scans, molecular dynamics, Monte Carlo, molecule gun) with any program that provides forces and energies. So you can study, at various levels of sophistication, the molecular and bulk properties of systems ranging from a few to a million atoms.

Polymer builder in GUI

Key features and benefits:

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Example application: sputtering

Sputtering atoms from a SiO2 surface for sputtering deposition. This can be done with all the tools in the Amsterdam Modeling Suite and requires the following steps

By reparametrizing the repulsive part of the ReaxFF bond parameters (ParAMS), we find good agreement with experimental sputtering yields at different incident angles and velocities.

Crystal orbital linear combinations

Perovskite band gaps, DOS and COOP

A tutorial illustrates how the analysis of density of states (DOS) and crystal-orbital overlap populations (COOP) provides insights about the nature of chemical bonding within crystalline materials. Relativity strongly influences the electronic structure of the heavy Pb and Cs atoms, and thereby the band gap of these perovskites. The relativistic calculations and in-depth bonding analysis helps to systematically tune the band gap in such crystals, which is of paramount importance for photoelectric and optoelectronic applications.


Tutorial: COOP analysis perovskite band structure

A webinar in 2017 highlighted recent papers and new capabilities for materials modeling (see slides and video), focusing for modeling properties of nanoparticles, batteries, and organic electronics. In 2020 we had a virtual hands-on workshop for periodic systems, including polymers.